tokenizer_class = get_class_from_dynamic_module(class_ref, pretrained_model_name_or_path, **kwargs) File "/home/knut/miniconda3/envs/textgen/lib/python3.10/site-packages/transformers/dynamic_module_utils.py", line 497, in get_class_from_dynamic_module return get_class_in_module(class_name...
@@ -106,17 +106,17 @@ def step_4_model(self, *args, **kwargs): 106 106 if not self.cfg.load and not self.cfg.resume: 107 107 self.model.create_from_pcd(self._pcd) 108 108 self.logger.info('create_from_pcd') 109 + storePly( 110 + self.output.joinpath('init_points...
(weight_path) model.set_dict(param) return model def resnet18(pretrained=False, **kwargs): """ResNet 18-layer model from `"Deep Residual Learning for Image Recognition" <https://arxiv.org/pdf/1512.03385.pdf>`_ Args: pretrained (bool, optional): If True, returns a model pre-trained ...
model = attempt_load(weights, map_location=device) # load FP32 model File "E:\yolov5\models\experimental.py", line 118, in attempt_load ckpt = torch.load(w, map_location=map_location) # load File "D:\Anaconda\envs\Smart_Garbage_Can\lib\site-packages\torch\serialization.py", line 809...
classVoxelResBackBone8x(nn.Module):def__init__(self,model_cfg,input_channels,grid_size,**kwargs):super().__init__()self.model_cfg=model_cfgnorm_fn=partial(nn.BatchNorm1d,eps=1e-3,momentum=0.01)# 固定参数eps和momentumself.sparse_shape=grid_size[::-1]+[1,0,0]# array([41, 1440...
/usr/bin/env python"""Copyright (c) 2006-2019 sqlmap developers (http://sqlmap.org/)See the file 'LICENSE' for copying permission"""importreimportphpserializefromlib.core.enumsimportPRIORITY__priority__=PRIORITY.NORMALdefdependencies():passdeftamper(payload,**kwargs):retVal=payloadifpayload:...
= 'wav': output_kwargs['codec'] = _to_ffmpeg_codec(codec) process = ( ffmpeg .input('pipe:', format='f32le', **input_kwargs) .output(path, **output_kwargs) .overwrite_output() .run_async(pipe_stdin=True, pipe_stderr=True, quiet=True)) process.stdin.write(data.astype('<f4...
"}) response = model(messages) print(response)面对过去，不要迷离；面对未来，不必彷徨；活在今天，...
latent_model_input, timestep, encoder_hidden_states=prompt_embeds, cross_attention_kwargs=self.cross_attention_kwargs, down_block_additional_residuals=down_block_res_samples, mid_block_additional_residual=mid_block_res_sample, added_cond_kwargs=added_cond_kwargs, ).sample alpha_prod...
Thread(target=runffmpeg, args=(ffmpegars,), kwargs={"noextname": self.noextname}).start() try: # 识别、创建字幕文件、翻译 if os.path.exists(self.sub_name) and os.path.getsize(self.sub_name) > 1: set_process(f"{self.noextname} 等待编辑字幕", "wait_subtitle") config....